Inferring purchase intent using non-payment transaction events

ABSTRACT

Inferring purchase intent using non-payment transaction signals predicts whether a payment transaction has been completed based on non-payment information. An account system that operates outside of the payment path does not take part in and the approval of a financial transaction between the user and the merchant system, distributes an offer to the user. The user completes a financial payment transaction with the merchant and the account system determines whether a trigger event has occurred. The user performs an action or enters information using the user computing device, and the user computing device transmits an indication of the action to the account system. In another example, the account system receives notification from another system or device. The account system determines whether the action is a trigger event and the predictive model determines whether the user completed a financial transaction and/or redeemed the distributed offer.

TECHNICAL FIELD

The present disclosure relates to inferring completion of a consumerpurchase transaction, providing improved data gathering, improvedunderstanding of how products are being used, and improved logging oftransactions outside of the financial transaction path and withoutconfirmation of a payment transaction.

BACKGROUND

In a conventional merchant-consumer financial transaction, the consumerprovides financial account information to the merchant by way of swipinga card, entering the account number, scanning a code comprising theaccount number, reading the account number to the merchant, or otherwisetransmitting the account number to a merchant system. The merchantsystem's point of sale terminal or online payment processor submits apayment request to the issuer of the account through the correspondingcard network. If funds are available, the issuer sends an authorizationcode to the merchant system to signal approval of the paymenttransaction. Systems and devices that are outside of or not a part ofthe financial transaction path are not notified and are unable todetermine that the financial transaction was approved and completedunless the merchant or consumer provide confirmation of the completion.

SUMMARY

In certain example aspects described herein, inferring purchase intentusing non-payment transaction signals comprises predicting whether apayment transaction has been completed based on non-payment information.An account management system that operates outside of the financialpayment path and does not take part in does not take part in theapproval of a financial transaction between the user and the merchantsystem, distributes an offer to the user. In another example embodiment,the account management system does not receive a notification that theoffer was redeemed and does not take part in the redemption of the offeroutside of distributing the offer to the user. However, the accountmanagement system infers the completion of the payment transactionbetween the user and the merchant system based on one or morenon-payment transaction signals.

The user completes a financial payment transaction with the merchantsystem and the account management system determines whether a triggerevent has occurred. The user performs an action or enters informationusing a user computing device, and the user computing device transmitsan indication of the action to the account management system. In anotherexample, the account management system receives notification fromanother system or device. The account management system determineswhether the action is a trigger event and determines whether the usercompleted a financial transaction and/or redeemed the distributed offerbased on the triggering event.

These and other aspects, objects, features, and advantages of theexample embodiments will become apparent to those having ordinary skillin the art upon consideration of the following detailed description ofillustrated example embodiments.

BRIEF DESCRIPTION OF THE DRAWINGS

FIG. 1 is a block diagram depicting a purchase inference system, inaccordance with certain example embodiments.

FIG. 2 is a block flow diagram depicting a method for inferring purchaseintent using non-purchase payment transaction signals, in accordancewith certain example embodiments.

FIG. 3 is a block flow diagram depicting a method for determining that atrigger event has occurred, in accordance with certain exampleembodiments.

FIG. 4 is a block diagram depicting a computing machine and module, inaccordance with certain example embodiments.

DETAILED DESCRIPTION OF THE EXAMPLE EMBODIMENTS

Overview

The example embodiments described herein provide methods and systemsthat enable inferring purchase intent using non-payment transactionsignals. In an example embodiment, a user completes a purchasetransaction with a merchant system. An account management system is nota part of the purchase transaction and therefore, outside of thefinancial transaction path (for example, the account management systemis not the merchant system, the issuer system, or any other systeminvolved in the approval or processing of the financial transaction).However, the account management system infers the completion of thepayment transaction between the user and the merchant system based onone or more non-payment transaction signals.

In an example embodiment, an account management system creates apredictive model or trains a classifier model to predict whether apayment transaction has been completed based on non-payment information.In an example embodiment, the predictive model is an artificial neuralnetwork or other form of adaptive system model, wherein the systemanalyzes data and relationships to find patterns in data. In anotherexample embodiment, the classifier model is a Gaussian Mixture Model,decision tree, Markov Decision Process, or other mathematical frameworkfor modeling decision making. In an example embodiment, the model istrained based on historical transaction data to predict when a paymenttransaction has occurred based on non-payment signal data received bythe account management system. In an example embodiment, the process isan ongoing learning process, wherein data is continuously added to theaccount management system and the model is continuously updated. In anexample embodiment, a user operating the user computing device enables apayment transaction prediction feature on the user computing device.

The account management system distributes an offer to the user. In anexample embodiment, the account management system logs an indicationthat the offer was distributed to, viewed by, or saved by the user. Inan example embodiment, the account management system operates outside ofthe financial payment path and does not take part in the approval of afinancial transaction between the user and the merchant system. Inanother example embodiment, the account management system does notreceive a notification that the offer was redeemed and does not takepart in the redemption of the offer outside of distributing the offer tothe user. For example, the offer distributed to the user comprises anindication that the Merchant X is having a sale on Product B. However,the user is not required to present the offer to receive the sale priceon Product B. In this example, the account management system presentedthe offer to the user and may have knowledge that the user viewed theoffer, but it does not have knowledge as to whether the user completed apurchase with Merchant X.

The user completes a financial payment transaction with the merchantsystem. The user may or may not redeem the offer distributed by theaccount management system as a part of the financial paymenttransaction. The account management system determines whether a triggerevent has occurred. In an example embodiment, the account managementsystem continuously monitors for a trigger event to occur. In thisembodiment, the account management system is not a part of the financialpayment transaction, so it determines that a transaction occurred bymonitoring for specified triggering events. In an example embodiment,the user performs an action or enters information using the usercomputing device. In an example embodiment, the user computing devicelogs the action, a location where the action occurred, and/or a timethat the action occurred. The user computing device transmits anindication of the action to the account management system and theaccount management system determines whether the action is a triggerevent. For example, the user may access a saved offer or financialaccount information at a merchant location. The user may mark a giftcard as redeemed or manually adjust a gift card balance in a digitalwallet application on the user computing device. In another exampleembodiment, the account management system receives notification fromanother system or device, for example a gift card system or a loyaltysystem. For example, the user registered or linked a gift card orloyalty account to the user's digital wallet account managed by theaccount management system. The account management system receives anotification from a system managing the gift card that the balance haschanged or from the system managing the loyalty account that the loyaltybalance has changed. In another example embodiment, the user manuallyadjusts the gift card and/or loyalty account balance. In another exampleembodiment, the account management system receives a copy of the paymentreceipt. In this example embodiment, the account management system iscapable of extracting information from the receipt and determining thatthe receipt is for a payment transaction. In another example embodiment,the user computing device may transmit a notification that the user wasin the merchant's retail location. The account management system usesthe logged trigger events to determine that the user completed afinancial transaction and also to determine that the user redeemed thedistributed offer.

By using and relying on the methods and systems described herein, theaccount management system is able to infer that the purchase transactionwas completed without being a part of the transaction or receivingpayment transaction signals. As such, the systems and methods describedherein may be employed to close the loop for offer systems and enablethe system to determine performance-based pricing for offers without theoffer system having to be a part of the offer redemption, to provide newor additional content to the user, and to more accurately determinewhich offers to provide to a user. The systems and methods describedherein may also be employed to provide a more accurate and expeditedunderstanding of how products (for example, gift cards) are being used.Additionally, the systems and methods described herein may also beemployed to provide the user with up-to-date and accurate records ofpurchases made. Hence, the systems and methods described herein bridgethe gap between the online and offline worlds and allow for theinteraction between different types of computing technologies (forexample, merchant point-of-sale devices, user mobile computing devices,and account management system computing devices) to achieve improveddata gathering, improved understanding of how products are being used,and improved logging of transactions outside of the financialtransaction path and without confirmation of a payment transaction.

Various example embodiments will be explained in more detail in thefollowing description, read in conjunction with the figures illustratingthe program flow.

Example System Architectures

Turning now to the drawings, in which like numerals indicate like (butnot necessarily identical) elements throughout the figures, exampleembodiments are described in detail.

FIG. 1 is a block diagram depicting a purchase inference system, inaccordance with certain example embodiments. As depicted in FIG. 1, theexemplary operating environment 100 comprises a user computing device110, a merchant computing system 120, and an account managementcomputing system 140 that are configured to communicate with one anothervia one or more networks 130. In another example embodiment, two or moreof these systems (including systems 110, 120, and 140) are integratedinto the same system. In some embodiments, a user associated with adevice must install an application and/or make a feature selection toobtain the benefits of the techniques described herein.

Each network 130 includes a wired or wireless telecommunication means bywhich network systems (including systems 110, 120, and 140) cancommunicate and exchange data. For example, each network 130 can beimplemented as, or may be a part of, a storage area network (SAN),personal area network (PAN), a metropolitan area network (MAN), a localarea network (LAN), a wide area network (WAN), a wireless local areanetwork (WLAN), a virtual private network (VPN), an intranet, anInternet, a mobile telephone network, a card network, Bluetooth,Bluetooth Low Energy (BLE), near field communication network (NFC), anyform of standardized radio frequency, infrared, sound (for example,audible sounds, melodies, and ultrasound), other short rangecommunication channel, or any combination thereof, or any otherappropriate architecture or system that facilitates the communication ofsignals, data, and/or messages (generally referred to as data).Throughout this specification, it should be understood that the terms“data” and “information” are used interchangeably herein to refer totext, images, audio, video, or any other form of information that canexist in a computer-based environment.

In an example embodiment, each network computing system (includingsystems 110, 120, and 140) includes a device having a communicationmodule capable of transmitting and receiving data over the network 130.For example, each network system (including systems 110, 120, and 140)may comprise a server, personal computer, mobile device (for example,notebook computer, tablet computer, netbook computer, personal digitalassistant (PDA), video game device, GPS locator device, cellulartelephone, Smartphone, or other mobile device), a television with one ormore processors embedded therein and/or coupled thereto, or otherappropriate technology that includes or is coupled to a web browser orother application for communicating via the network 130. In the exampleembodiment depicted in FIG. 1, the network computing systems (includingsystems 110, 120, and 140) are operated by users, merchants, and accountmanagement system operators, respectively.

The merchant computing system 120 comprises at least one point of sale(POS) terminal 121 that is capable of processing a purchase transactioninitiated by a user, for example, a cash register. In an exampleembodiment, the merchant operates a commercial store and the userindicates a desire to make a purchase by presenting a form of payment atthe POS terminal 121. In another example embodiment, the merchantoperates an online store and the user indicates a desire to make apurchase by clicking a link or “checkout” button on a website. Inanother example embodiment, the user computing device 110 is configuredto perform the functions of the POS terminal 121. In this example, theuser scans and/or pays for the transaction via the user computing device110 without interacting with the POS terminal 121.

In an example embodiment, the merchant system 120 is capable ofcommunicating with the account management system 140 via a merchantcomputing device 125 and an application 127. The merchant computingdevice 125 may be an integrated part of the POS terminal or a standalonehardware device, in accordance with alternative example embodiments.

In an example embodiment, the user computing device 110 may be apersonal computer, mobile device (for example, notebook, computer,tablet computer, netbook computer, personal digital assistant (PDA),video game device, GPS locator device, cellular telephone, Smartphone orother mobile device), television, wearable computing devices (forexample, watches, rings, or glasses), or other appropriate technologythat includes or is coupled to a web server, or other suitableapplication for interacting with the account management system 140. Theuser can use the user computing device 110 to view offers distributed bythe account management system 140 via a user interface 111 and anapplication 115. The application 115 is a program, function, routine,applet or similar entity that exists on and performs its operations onthe user computing device 110. For example, the application 115 may beone or more of a shopping application, a merchant system 120application, an account management system 140 application, an Internetbrowser, a digital wallet application, a loyalty card application,another value-added application, a user interface 111 application, orother suitable application operating on the user computing device 110.In some embodiments, the user must install an application 115 and/ormake a feature selection on the user computing device 110 to obtain thebenefits of the techniques described herein.

In an example embodiment, selected offers, financial accountinformation, loyalty account information, gift card account information,and related information is stored in the data storage unit 117. In anexample embodiment, the data storage unit 117 and application 115 may beimplemented in a secure element or other secure memory (not shown) onthe user computing device 110. In another example embodiment, the datastorage unit 117 may be a separate memory unit resident on the usercomputing device 110. In an example embodiment, the data storage unit117 can include any local or remote data storage structure accessible tothe user computing device 110 suitable for storing information. In anexample embodiment, the data storage unit 117 stores encryptedinformation, such as HTML5 local storage.

An example user computing device 110 communicates with the accountmanagement system 140. An example account management system 140comprises an offer distribution module 141, account module 143, aredemption prediction module 145, and a data storage unit 147. Anexample offer distribution module 141 receives offers from the merchantsystem 120 or a third party system and distributes the offers to usersfor review and selection. In another example embodiment, the offersystem 140 may generate web-based user interfaces providing forms forthe merchant system 120 or third party system to create offers. Theoffers may be prepaid offers, wherein the user pays a specified amountfor the offer prior to redeeming the offer with the merchant system 120.In another example embodiment, the offers may be advertisements orpresent information to the user. In this example embodiment, the accountmanagement system 140 does not receive a notification that the offer wasredeemed and does not take part in the redemption of the offer outsideof distributing the offer to the user. For example, the offerdistributed to the user comprises an indication that the Merchant X ishaving a sale on Product B. However, the user is not required to presentthe offer to receive the sale price on Product B. In this example, theaccount management system 140 presented the offer to the user, and mayhave knowledge that the user viewed the offer, but it does not haveknowledge as to whether the user completed a purchase with Merchant X.

In an example embodiment, the user selects the offer distributed by theaccount management system 140. In an example embodiment, the userselects an offer by clicking on it and saving it in the user's digitalwallet application 115, which may then be uploaded to the accountmanagement system 140 and associated with the user's account. If theoffer is a prepaid offer, then the user may pay for the offer prior tosaving the offer in the user's digital wallet application 115. Inexample embodiment, an offer may be displayed in the form of a voucheror coupon in response to user's Internet search. In an alternativeexample embodiment, the user can use a smart phone application 115 toselect the offer.

In an example embodiment, the account module 143 manages theregistration of user and maintains an account for the user. In anexample embodiment, the user account module 143 may collect anonymous,non-personal information for the user. For example, the user accountmodule 143 may generate an anonymous user account identifier, such thatthe user is not personally identifiable. In another example embodiment,the user account module 143 may generate web-based user interfacesproviding forms for the user to optionally register for an accountmanagement system 140 account.

The redemption prediction module 145 gathers historical transaction datato predict when a payment transaction has occurred based on non-paymentsignal data received by the account management system. In an exampleembodiment, the redemption prediction module 145 analyzes the data andlearns to identify features, events, and/or signals that correspond tothe completion of a purchase transaction and to detect patterns thatwill aid in the identification of when a purchase transaction hasoccurred. In an example embodiment, the redemption prediction module 145creates a prediction model. The prediction model is an artificial neuralnetwork or other form of adaptive system model, wherein the redemptionprediction module 145 analyzes data and relationships to find patternsin data. In an example embodiment, this process is an ongoing learningprocess, wherein data is continuously added to the redemption predictionmodule 145 and the model is continuously updated. In an exampleembodiment, the data is saved in the data storage unit 147.

In an example embodiment, the data storage unit 147 can include anylocal or remote data storage structure accessible to the accountmanagement system 140 suitable for storing information. In an exampleembodiment, the data storage unit 147 stores encrypted information, suchas HTML5 local storage.

In example embodiments, the network computing devices and any othercomputing machines associated with the technology presented herein maybe any type of computing machine such as, but not limited to, thosediscussed in more detail with respect to FIG. 4. Furthermore, anymodules associated with any of these computing machines, such as modulesdescribed herein or any other modules (scripts, web content, software,firmware, or hardware) associated with the technology presented hereinmay by any of the modules discussed in more detail with respect to FIG.4. The computing machines discussed herein may communicate with oneanother as well as other computer machines or communication systems overone or more networks, such as network 130. The network 130 may includeany type of data or communications network, including any of the networktechnology discussed with respect to FIG. 4.

The components of the example operating environment 100 are describedhereinafter with reference to the example methods illustrated in FIGS.2-3. The example methods of FIGS. 2-3 may also be performed with othersystems and in other environments.

Example System Processes

FIG. 2 is a block flow diagram depicting a method for inferring purchaseintent using non-purchase payment transaction signals, in accordancewith certain example embodiments. The method 200 is described withreference to the components illustrated in FIG. 1.

In block 210, the account management system 140 creates a predictivemodel or classifier to that will be used to predict whether the usercompleted a financial purchase transaction with a merchant and/orredeemed an offer. In an example embodiment, the predictive model orclassifier is an artificial neural network or other form of adaptivesystem model, wherein the model analyzes data and relationships to findpatterns in data. An artificial neural network is a computational modulethat functions to process information, such as studying behavior,pattern recognition, forecasting, and data compression. An examplepredictive model or classifier may be hardware and software based orpurely software based and run in computer models. In an exampleembodiment, the predictive model or classifier model comprises inputs(for example changes in gift card or loyalty account balances,selections of a saved offer, location data that corresponds to amerchant location, display of financial data, display of an offer,receipt data, and other data that suggests a financial transaction wascompleted) that are multiplied by weights and then computed by amathematical function to determine the output (for example, thelikelihood that a financial transaction was completed or an offer wasredeemed). Depending on the weights, the computation will be different.In an example embodiment, an algorithm is used to adjust the weights ofthe predictive model or classifier in order to obtain the desired outputfrom the network (for example, to accurately identify that a financialtransaction was completed or an offer was redeemed). In an exampleembodiment, this process is an ongoing learning process, whereinnon-payment transaction events are continuous added and themodel/classifier is updated. As more training data is fed into themodel, it will continuously improve.

In another example embodiment, the classifier model is a GaussianMixture Model, decision tree, Markov Decision Process, or othermathematical framework for modeling decision making. In an exampleembodiment, the model is trained based on historical data of a completedfinancial transaction or a redeemed offer to predict whether a financialtransaction was completed or an offer was redeemed based on the datareceived by the account management system 140. In an example embodiment,the process is an ongoing learning process, wherein data is continuouslyadded to the account management system 140 and the model is continuouslyupdated.

In block 220, an offer is created. In an example embodiment, an offer iscreated by a merchant, manufacturer, and/or alternative offer providerand distributed to potential users. An offer provides an incentive for auser to purchase a product. Throughout this specification, the term“product” refers to tangible and intangible products, includingservices.

In an example embodiment, the offer is a non-prepaid offer (for example,a loyalty reward, a coupon, discounts, or other offer redeemable with amerchant, manufacturer, service provider, and/or provider of goods). Inanother example embodiment, the offer is a prepaid offer and the userpays a predetermined price for the goods and/or services.

The merchant system 120 or other provider of the offer specifies theoffer details, by specifying the type of offer, the duration, the amountof the redemption, and additional pertinent redemption details whencreating the offer. In an example embodiment, the merchant system 120creates an offer by entering the offer details and redemption rules intoa merchant computing device 125 to create an electronic record for theoffer. In certain example embodiments, the merchant system 120 may inputthe offer details and redemption rules directly into the accountmanagement system 140 via the application 127 to create an electronicrecord for the offer in the account management system 140.

In an example embodiment, the merchant system 120 creates the offeroutside of the account management system 140. In another exampleembodiment, the account management system 140 may generate web-baseduser interfaces providing forms for the merchant system 120 to createoffers.

In block 225, the offer is distributed to the account management system140. In an example embodiment, the account management system 140receives the offer from the merchant, manufacturer, and/or alternativeoffer provider that created the offer. For example, the provider maycommunicate the electronic offer record to the account management system140 via the network 130. As discussed previously, in another embodiment,the provider may create the electronic record for the offer in theaccount management system 140. The offer distribution module 141receives the offer record and stores the offer record in the datastorage unit 147.

In block 230, the account management system 140 distributes the offer.For example, the account management system 140 distributes the offer viathe network 130 to multiple user computing devices 110 for presentationto the users via the user computing devices 110.

In an example embodiment, the account management system 140 distributesthe offer through network channels selected by the creator of the offer,including display on cost per mille impression (“CPM”), pay per click(“PPC”), electronic correspondence, offers near me, and otheradvertising methods. In an example embodiment, the offer is a pay perclick (“PPC”) offer, wherein the creator of the offer pays a service feeto the account management system 140 for each time the offer is clickedby a user. In another example example embodiment, the offer is a costper mille (“CPM”) or cost per thousand (“CPT”) offers, wherein thecreator of the offer pays a service fee to the offer system 140 forevery 1000 page views. In yet another example embodiment, the offer isdistributed through an “offers near me” model, wherein the offer isdisplayed in a selected search query that provides results that arephysically within a set distance from the user's location. The creatorof the offer may select multiple methods of distribution for the sameoffer. The creator of the offer may also create multiple offers to bedistributed through the same or different network channels.

In block 235, a user reviews one or more of the distributed offers thatare presented on the user computing device 110 and selects one or moreoffers distributed by the account management system 140. In an exampleembodiment, the user selects an offer by operating the user computingdevice 110 to click on the offer, to press a button to “save” the offer,or by other suitable input to indicate a desire to select and/or savethe offer. In another example embodiment, the offer is a prepaid offer,and the user selects the offer by purchasing the offer.

In block 240, the account management system 140 receives a notificationthat the user selected the offer. In an example embodiment, when theuser selects a particular offer, an electronic offer instance is createdand transmitted by the user computing device 110 to the accountmanagement system 140. In an example embodiment, the notification isreceived by the account module 143. In this embodiment, the notificationcomprises an identification of the user so that the account managementsystem 140 can identify the user's account management system 140account. In another example embodiment, the identification comprises anon-personal identifier (for example, an identification number or code).

In block 245, the account management system 140 saves an indication thatthe user selected the offer. In an example embodiment, the accountmanagement system 140 saves the electronic offer instance in the user'saccount management system 140 account.

In block 250, the user completes a purchase transaction with themerchant. In an example embodiment, the purchase transaction comprises acash transaction, a debit transaction, a credit transaction, a loyaltypoint redemption transaction, a prepaid transaction, or other form ofpurchase transaction. In an example embodiment, the account managementsystem 140 does not participate in the purchase transaction. In thisembodiment, the purchase transaction is processed according to theselected means and the account management system 140 is not notified ofthe desire to complete the transaction, approval of the financialtransaction, or completion of the payment transaction. In an exampleembodiment, an issuer system, other than the account management system140 approves a financial payment transaction and notifies the merchantsystem 120 of the approval.

In an example embodiment, the offer selected by the user is redeemedduring the purchase transaction. In an example embodiment, the accountmanagement system 140 does not participate in the redemption of theoffer. In this embodiment, the account management system 140 does notparticipate in the authorization, approval, or fraud verification of theoffer when it is being redeemed. For example, the offer distributed tothe user comprises an indication that the Merchant X is having a sale onProduct B. However, the user is not required to present the offer toreceive the sale price on Product B. In this example, the accountmanagement system 140 presented the offer to the user, and may haveknowledge that the user viewed the offer, but it does not have knowledgeas to whether the user completed a purchase with Merchant X.

In another example, the offer comprises a notification that Merchant Zis having a store-wide sale. However, the user is not required topresent the offer to receive the benefit of the sale. In this example,the account management system 140 presented the offer to the user, andmay have knowledge that the user viewed the offer, but it does not haveknowledge as to whether the user completed a purchase with Merchant Z.

In yet another example, the offer comprises a manufacturer offer forProduct C. However, the redemption of the offer is processed by themerchant system 120 and/or the manufacturer of Product C. In thisexample, the account management system 140 presented the offer to theuser, and may have knowledge that the user viewed the offer, but it doesnot have knowledge as to whether the user completed a purchase ofProduct C.

In an example embodiment, the user uses the user computing device 110 toperform an action prior to, during, or after the purchase transaction.In an example embodiment, the action is not required for the purchasetransaction and/or offer redemption to be completed. For example, theuser access the user computing device 110 in the merchant location, anoffer, gift account information, loyalty account information, orfinancial account information is presented by the user computing device110, the user adjusts an account balance, directions are requested, orother action performed by the user computing device 110. In an exampleembodiment, the user computing device 110 logs the action, a locationwhere the action occurred, and/or a time that the action occurred. In anexample embodiment, the user computing device 110 transmits a notationof the action to the account management system 140. In another exampleembodiment, the account management system 140 is continuously monitoringor communicating with the user computing device 110 to detect when theuser computing device 110 logs an action. In this example embodiment,the user enables a feature or option on the user computing device 110 toallow the device 110 to log the actions.

In block 260, the account management system 140 determines whether oneor more trigger events have occurred. In an example embodiment, atrigger event comprises a signal, data, or other indication that may beused by the predictive model to determine a likelihood that a purchasetransaction occurred and/or an offer was redeemed. In an exampleembodiment, the signals are received by the account management system140 from the user computing device 110. In this example embodiment, theuser enables a feature or option on the user computing device 110 toallow the device 110 to transmit notification of the signals to theaccount management system 140. In another example embodiment, thesignals are received from one or more other systems. For example, aloyalty account system, a gift card account system, a receipt managementsystem, or other non-account management system 140. In this embodiment,the user enables a feature or option to enable the system to transmitnotifications to the account management system 140. The method fordetermining that a trigger event has occurred is described in moredetail hereinafter with reference to the methods described in FIG. 3.

FIG. 3 is a block flow diagram depicting a method 260 for determiningthat a trigger event has occurred, in accordance with certain exampleembodiments, as referenced in block 260. The method 260 is describedwith reference to the components illustrated in FIG. 1.

In block 310, the user computing device 110 transmits an indication thata user action has been taken. In an example embodiment, the usercomputing device 110 continuously monitors for a number of user actions,for example, changes in user computing device 110 location, display ofinformation on the user interface 111, account updates, receipt ofinformation, and other actions determined by the predictive model to berelated to a purchase transaction. In an example embodiment, a locationof the user computing device 110 and a time is determined when theaction is detected. In an example embodiment, the account managementsystem 140 communicates new actions and updates to the user computingdevice 110 as the predictive model is updated. In another exampleembodiment, a system (for example, a loyalty account system, a gift cardaccount system, a receipt management system, or other non-accountmanagement system 140) transmits the indication that the user action hasbeen taken.

In block 320, the account management system 140 receives the indicationthat the user action has been taken. In an example embodiment, theindication comprises and identification of the user or an identifierthat allows the account management system 140 to identify the user'saccount management system 140 account. In an example embodiment, theaccount management system 140 saves the indication in the user'saccount.

In an example embodiment, the account management system determineswhether the indication comprises a trigger event. In an exampleembodiment, a trigger event comprises a signal, data, or otherindication that may be used by the predictive model to determine alikelihood that a purchase transaction occurred and/or an offer wasredeemed. In an example embodiment, the account management system 140uses the indicated action in combination with a time that the actiontook place and/or a location of the user computing device 110 todetermine a likelihood that a purchase transaction occurred and/or anoffer was redeemed. In another example embodiment, the accountmanagement system 140 assigns weights to particular actions to determinea likelihood that a purchase transaction occurred and/or an offer wasredeemed. For example, if an offer or financial account information wasdisplayed at a merchant location, a greater weight may be assigned thanif the same action was taken at a non-merchant location.

In block 330, the account management system 140 determines whether theindication comprises a change in a gift card balance. In an exampleembodiment, the user has associated or registered a gift card with theuser's account management system 140 account. In this embodiment, theuser may manually enter the account management system 140 account andupdate the gift card balance. In another example embodiment, the usermay use an application 115 on the user computing device 110 to updatethe gift card balance. In yet another example embodiment, the accountmanagement system 140 may receive a notification of the change in giftcard balance from a system that manages the user's gift card account.

If the account management system 140 determines that the indicationcomprises a change in a gift card balance, the method 260 proceeds toblock 335 and the account management system logs the indication as atrigger event.

The method 260 then proceeds to block 340.

Returning to block 330, if the account management system 140 determinesthat the indication does not comprise a change in a gift card balance,the method 260 proceeds to block 340.

In block 340, the account management system 140 determines whether theindication comprises a change in a merchant loyalty account balance. Inan example embodiment, the user has associated or registered a loyaltyaccount with the user's account management system 140 account. In thisembodiment, the user may manually enter the account management system140 account and update the loyalty account balance. In another exampleembodiment, the user may use an application 115 on the user computingdevice 110 to update the loyalty account balance. In yet another exampleembodiment, the account management system 140 may receive a notificationof the change in loyalty account balance from a system that manages theuser's loyalty account.

If the account management system 140 determines that the indicationcomprises a change in a loyalty account balance, the method 260 proceedsto block 345 and the account management system logs the indication as atrigger event.

The method 260 then proceeds to block 350.

Returning to block 340, if the account management system 140 determinesthat the indication does not comprise a change in a loyalty accountbalance, the method 260 proceeds to block 350.

In block 350, the account management system 140 determines whether theindication comprises a display of a gift card or loyalty card on theuser computing device 110. In an example embodiment, the user has savedan account identifier in the user computing device 110. When the useraccessed the saved account identifier, the user computing device 110displays the identifier for the user to read or present to the merchantsystem 120. In an example embodiment, the indication also comprises alocation of the user computing device 110 when the identifier wasdisplayed. In this embodiment, the account management system 140 usesthe location to determine whether it corresponds to a merchant location.

If the account management system 140 determines that the indicationcomprises a display of a gift card or loyalty card on the user computingdevice 110, the method 260 proceeds to block 355 and the accountmanagement system logs the indication as a trigger event.

The method 260 then proceeds to block 360.

Returning to block 350, if the account management system 140 determinesthat the indication does not comprise a display of a gift card orloyalty card on the user computing device 110, the method 260 proceedsto block 360.

In block 360, the account management system 140 determines whether theindication comprises a display of a financial account card on the usercomputing device 110. In an example embodiment, the user has saved anaccount identifier in the user computing device 110. When the useraccessed the saved account identifier, the user computing device 110displays the identifier for the user to read or present to the merchantsystem 120. In an example embodiment, the indication also comprises alocation of the user computing device 110 when the identifier wasdisplayed. In this embodiment, the account management system 140 usesthe location to determine whether it corresponds to a merchant location.

If the account management system 140 determines that the indicationcomprises a display of a financial account card on the user computingdevice 110, the method 260 proceeds to block 365 and the accountmanagement system logs the indication as a trigger event.

The method 260 then proceeds to block 370.

Returning to block 360, if the account management system 140 determinesthat the indication does not comprise a display of a financial accountcard on the user computing device 110, the method 260 proceeds to block370.

In block 370, the account management system 140 determines whether theindication comprises a transaction receipt. In an example embodiment,the user has associated or registered an electronic message (e-mail)account with the user's account management system 140 account. In thisembodiment, the user may opt to receive an electronic version of thetransaction receipt for the purchase transaction via e-mail. The accountmanagement system 140 reviews the e-mail message to determine if itcomprises a receipt. In another example embodiment, the user may scan ormanually enter the transaction receipt into the user's accountmanagement system 140 account. In another example embodiment, theaccount management system 140 extracts information from the receipt. Forexample, purchase information, merchant name, and other information thatidentifies the purchase and whether an offer was redeemed.

If the account management system 140 determines that the indicationcomprises a transaction receipt, the method 260 proceeds to block 375and the account management system logs the indication as a triggerevent.

The method 260 then proceeds to block 380.

Returning to block 370, if the account management system 140 determinesthat the indication does not comprise a purchase receipt, the method 260proceeds to block 380.

In block 380, the account management system 140 determines whether theindication comprises a display of an offer on the user computing device110. In an example embodiment, the user has saved the offer in the usercomputing device 110 or in the user's account management system 140account. When the user accessed the saved offer, the user computingdevice 110 displays the offer for the user to read or present to themerchant system 120. In an example embodiment, the indication alsocomprises a location of the user computing device 110. In an exampleembodiment, the user computing device 110 was located at the merchantlocation when the offer was presented. In this embodiment, the accountmanagement system 140 uses the location to determine whether itcorresponds to a merchant location.

If the account management system 140 determines that the indicationcomprises a display of an offer on the user computing device 110, themethod 260 proceeds to block 385 and the account management system logsthe indication as a trigger event.

In an example embodiment, the account management system 140 adds andmodifies the events or signals it looks for in the indications based onthe predictive model. For example, if the predictive model determinesthat the user entering search criteria for a merchant location and thenthe user computing device 110 being located at the merchant location isa factor that may indicate that the user completed a purchasetransaction, the account management system will make the appropriatedetermination when evaluating whether a trigger event has occurred.

The method 260 then proceeds to block 270 in FIG. 2.

Returning to FIG. 2, in block 270, the account management system 140determines that the user redeemed an offer in connection with thecompleted purchase transaction. In an example embodiment, the accountmanagement system 140 uses the one or more trigger events to determinewhether the user completed a purchase transaction and redeemed an offer.

In an example embodiment, the account management system 140 retrievesthe electronic offer instance or other indication that the user selectedthe offer distributed by the account management system 140. The accountmanagement system 140 reviews the offer instance and determines themerchant computing system 120 associated with the offer instance. Forexample, the account management system 140 determines the merchantlocation(s) and/or merchant name. In an example embodiment, the accountmanagement system 140 reviews the recorded trigger events to determine alikelihood that each event is associated with the offer by determining alikelihood that each event is associated with the merchant location(s)and/or merchant name associated with the offer instance.

In an example embodiment, the account management system 140 reviews therecorded trigger events to determine a likelihood that the usercompleted a purchase transaction and redeemed an offer. In an exampleembodiment, the recorded trigger events are weighted based on a strengthof the trigger event and/or the likelihood that the trigger eventresulted from the user completed a purchase transaction and redeemed anoffer. For example, if a change in a gift card balance is detected, theaccount management system 140 may assign a lower weight if the gift cardis available for use at multiple merchants (for example, a Issuer A GiftCard) than if the gift card is available for use at a single merchant(for example, a Merchant X Gift Card). In another example, the accountmanagement system 140 may assign a higher weight to a change in amerchant loyalty account or gift card balance than a detection that theloyalty account or gift card information has been displayed.

The recorded trigger events can be viewed in conjunction with oneanother. For example, the recorded location of the user computing device110 is at the merchant location. The recorded location of user computingdevice 110 can be used in connection with other signals to provide agreater likelihood that the action was taken in connection with apurchase transaction and redemption of an offer. For example, if theuser computing device 110 displays financial account information or theoffer and the location of the user computing device 110 is at themerchant location at a time when the information was displayed, theaccount management system 140 will assign a higher weight to triggerevent, resulting in a higher likelihood that the user completed apurchase transaction and redeemed an offer. In another example, theaccount management system 140 determines the probability that the changein Gift Card A balance and the user computing device 110 having beenlocated at a location of Merchant X is due to the user completing apurchase transaction with Merchant X and/or redeeming Offer Z. In anexample embodiment, the location of the user computing device 110 atMerchant X provides an additional trigger event signal to aid in thedetermination that the purchase transaction occurred. In an exampleembodiment, other data, for example an indication that Gift Card A canonly be redeemed at a limited number of merchants provides additionaltrigger event signal data. Multiple trigger event signals can be used tocalculate the probable reason for the data.

In an example embodiment, the weighted trigger events are reviewed and alikelihood that the trigger events are related to the recorded offerinstance. In an example embodiment, the trigger events are weighed byand the determination is made using the predictive model. In thisexample embodiment, the trigger event data is added to the predictivemodel and the model determines a probability that the trigger eventsoccurred because the user completed a purchase transaction and/orredeemed the offer.

In block 275, the account management system 140 assigns a confidencevalue to the determination whether a purchase transaction was completedand/or an offer was redeemed. In an example embodiment, the confidencevalue is obtained by calculating a likelihood that the determination iscorrect. For example, a greater confidence value may be assigned when agreater number of trigger events are received and a lower confidencevalue may be assigned when a lower number of trigger events arereceived. In another example, the confidence value may result from or becalculated using the weights assigned to each trigger event. In thisexample, a weighted average can be calculated and compared to a set ofpre-determined threshold values to determine the confidence value.

In another example embodiment, the confidence value is obtained bycalculating a likelihood that the determination is correct given thetrained model or classifier. For example, the account management system140 determines whether similar trigger event signal data have beenpreviously received that corresponded to the completion of a purchasetransaction and/or redemption of an offer. In an example embodiment, newtrigger event signals are received and the predictive model uses the newsignals in combination with previously received signals to make thedetermination.

In block 280, the account management system 140 updates the predictivemodel or classifier model based on the trigger event signal data. In anexample embodiment, the process is an ongoing learning process, whereindata is continuously added to the account management system 140 and themodel is continuously updated.

In block 290, the account management system 140 determines that theconfidence value is over a pre-determined threshold value, andaccordingly that the user completed a purchase transaction and redeemedthe offer. In an example embodiment, the account management system 140marks the offer as redeemed.

In an example embodiment, the account management system 140 determinedthat a purchase transaction has likely occurred between the merchant andthe user based on the trigger events and the information known about theoffer in the offer instance. The account management system 140determines a probability that the offer was redeemed and marks itaccordingly.

In an example embodiment, the account management system 140 updates theuser's account management system 140 account and distributes anadditional offer to the user based on the knowledge that the userredeemed the previous offer. In another example embodiment, the accountmanagement system 140 logs the redemption of the offer and transmits arecord of the number of redemptions, the redemption rate, or otherredemption-related data to the merchant system 120 or offer creator.

Other Example Embodiments

FIG. 4 depicts a computing machine 2000 and a module 2050 in accordancewith certain example embodiments. The computing machine 2000 maycorrespond to any of the various computers, servers, mobile devices,embedded systems, or computing systems presented herein. The module 2050may comprise one or more hardware or software elements configured tofacilitate the computing machine 2000 in performing the various methodsand processing functions presented herein. The computing machine 2000may include various internal or attached components such as a processor2010, system bus 2020, system memory 2030, storage media 2040,input/output interface 2060, and a network interface 2070 forcommunicating with a network 2080.

The computing machine 2000 may be implemented as a conventional computersystem, an embedded controller, a laptop, a server, a mobile device, asmartphone, a set-top box, a kiosk, a vehicular information system, onemore processors associated with a television, a customized machine, anyother hardware platform, or any combination or multiplicity thereof. Thecomputing machine 2000 may be a distributed system configured tofunction using multiple computing machines interconnected via a datanetwork or bus system.

The processor 2010 may be configured to execute code or instructions toperform the operations and functionality described herein, managerequest flow and address mappings, and to perform calculations andgenerate commands. The processor 2010 may be configured to monitor andcontrol the operation of the components in the computing machine 2000.The processor 2010 may be a general purpose processor, a processor core,a multiprocessor, a reconfigurable processor, a microcontroller, adigital signal processor (DSP), an application specific integratedcircuit (ASIC), a graphics processing unit (GPU), a field programmablegate array (FPGA), a programmable logic device (PLD), a controller, astate machine, gated logic, discrete hardware components, any otherprocessing unit, or any combination or multiplicity thereof. Theprocessor 2010 may be a single processing unit, multiple processingunits, a single processing core, multiple processing cores, specialpurpose processing cores, co-processors, or any combination thereof.According to certain embodiments, the processor 2010 along with othercomponents of the computing machine 2000 may be a virtualized computingmachine executing within one or more other computing machines.

The system memory 2030 may include non-volatile memories such asread-only memory (ROM), programmable read-only memory (PROM), erasableprogrammable read-only memory (EPROM), flash memory, or any other devicecapable of storing program instructions or data with or without appliedpower. The system memory 2030 may also include volatile memories such asrandom access memory (RAM), static random access memory (SRAM), dynamicrandom access memory (DRAM), and synchronous dynamic random accessmemory (SDRAM). Other types of RAM also may be used to implement thesystem memory 2030. The system memory 2030 may be implemented using asingle memory module or multiple memory modules. While the system memory2030 is depicted as being part of the computing machine 2000, oneskilled in the art will recognize that the system memory 2030 may beseparate from the computing machine 2000 without departing from thescope of the subject technology. It should also be appreciated that thesystem memory 2030 may include, or operate in conjunction with, anon-volatile storage device such as the storage media 2040.

The storage media 2040 may include a hard disk, a floppy disk, a compactdisc read only memory (CD-ROM), a digital versatile disc (DVD), aBlu-ray disc, a magnetic tape, a flash memory, other non-volatile memorydevice, a solid state drive (SSD), any magnetic storage device, anyoptical storage device, any electrical storage device, any semiconductorstorage device, any physical-based storage device, any other datastorage device, or any combination or multiplicity thereof. The storagemedia 2040 may store one or more operating systems, application programsand program modules such as module 2050, data, or any other information.The storage media 2040 may be part of, or connected to, the computingmachine 2000. The storage media 2040 may also be part of one or moreother computing machines that are in communication with the computingmachine 2000 such as servers, database servers, cloud storage, networkattached storage, and so forth.

The module 2050 may comprise one or more hardware or software elementsconfigured to facilitate the computing machine 2000 with performing thevarious methods and processing functions presented herein. The module2050 may include one or more sequences of instructions stored assoftware or firmware in association with the system memory 2030, thestorage media 2040, or both. The storage media 2040 may thereforerepresent examples of machine or computer readable media on whichinstructions or code may be stored for execution by the processor 2010.Machine or computer readable media may generally refer to any medium ormedia used to provide instructions to the processor 2010. Such machineor computer readable media associated with the module 2050 may comprisea computer software product. It should be appreciated that a computersoftware product comprising the module 2050 may also be associated withone or more processes or methods for delivering the module 2050 to thecomputing machine 2000 via the network 2080, any signal-bearing medium,or any other communication or delivery technology. The module 2050 mayalso comprise hardware circuits or information for configuring hardwarecircuits such as microcode or configuration information for an FPGA orother PLD.

The input/output (I/O) interface 2060 may be configured to couple to oneor more external devices, to receive data from the one or more externaldevices, and to send data to the one or more external devices. Suchexternal devices along with the various internal devices may also beknown as peripheral devices. The I/O interface 2060 may include bothelectrical and physical connections for operably coupling the variousperipheral devices to the computing machine 2000 or the processor 2010.The I/O interface 2060 may be configured to communicate data, addresses,and control signals between the peripheral devices, the computingmachine 2000, or the processor 2010. The I/O interface 2060 may beconfigured to implement any standard interface, such as small computersystem interface (SCSI), serial-attached SCSI (SAS), fiber channel,peripheral component interconnect (PCI), PCI express (PCIe), serial bus,parallel bus, advanced technology attached (ATA), serial ATA (SATA),universal serial bus (USB), Thunderbolt, FireWire, various video buses,and the like. The I/O interface 2060 may be configured to implement onlyone interface or bus technology. Alternatively, the I/O interface 2060may be configured to implement multiple interfaces or bus technologies.The I/O interface 2060 may be configured as part of, all of, or tooperate in conjunction with, the system bus 2020. The I/O interface 2060may include one or more buffers for buffering transmissions between oneor more external devices, internal devices, the computing machine 2000,or the processor 2010.

The I/O interface 2060 may couple the computing machine 2000 to variousinput devices including mice, touch-screens, scanners, electronicdigitizers, sensors, receivers, touchpads, trackballs, cameras,microphones, keyboards, any other pointing devices, or any combinationsthereof. The I/O interface 2060 may couple the computing machine 2000 tovarious output devices including video displays, speakers, printers,projectors, tactile feedback devices, automation control, roboticcomponents, actuators, motors, fans, solenoids, valves, pumps,transmitters, signal emitters, lights, and so forth.

The computing machine 2000 may operate in a networked environment usinglogical connections through the network interface 2070 to one or moreother systems or computing machines across the network 2080. The network2080 may include wide area networks (WAN), local area networks (LAN),intranets, the Internet, wireless access networks, wired networks,mobile networks, telephone networks, optical networks, or combinationsthereof. The network 2080 may be packet switched, circuit switched, ofany topology, and may use any communication protocol. Communicationlinks within the network 2080 may involve various digital or an analogcommunication media such as fiber optic cables, free-space optics,waveguides, electrical conductors, wireless links, antennas,radio-frequency communications, and so forth.

The processor 2010 may be connected to the other elements of thecomputing machine 2000 or the various peripherals discussed hereinthrough the system bus 2020. It should be appreciated that the systembus 2020 may be within the processor 2010, outside the processor 2010,or both. According to some embodiments, any of the processor 2010, theother elements of the computing machine 2000, or the various peripheralsdiscussed herein may be integrated into a single device such as a systemon chip (SOC), system on package (SOP), or ASIC device.

In situations in which the systems discussed here collect personalinformation about users, or may make use of personal information, theusers may be provided with an opportunity or option to control whetherprograms or features collect user information (e.g., information about auser's social network, social actions or activities, profession, auser's preferences, or a user's current location), or to control whetherand/or how to receive content from the content server that may be morerelevant to the user. In addition, certain data may be treated in one ormore ways before it is stored or used, so that personally identifiableinformation is removed. For example, a user's identity may be treated sothat no personally identifiable information can be determined for theuser, or a user's geographic location may be generalized where locationinformation is obtained (such as to a city, ZIP code, or state level),so that a particular location of a user cannot be determined. Thus, theuser may have control over how information is collected about the userand used by a content server.

Embodiments may comprise a computer program that embodies the functionsdescribed and illustrated herein, wherein the computer program isimplemented in a computer system that comprises instructions stored in amachine-readable medium and a processor that executes the instructions.However, it should be apparent that there could be many different waysof implementing embodiments in computer programming, and the embodimentsshould not be construed as limited to any one set of computer programinstructions. Further, a skilled programmer would be able to write sucha computer program to implement an embodiment of the disclosedembodiments based on the appended flow charts and associated descriptionin the application text. Therefore, disclosure of a particular set ofprogram code instructions is not considered necessary for an adequateunderstanding of how to make and use embodiments. Further, those skilledin the art will appreciate that one or more aspects of embodimentsdescribed herein may be performed by hardware, software, or acombination thereof, as may be embodied in one or more computingsystems. Moreover, any reference to an act being performed by a computershould not be construed as being performed by a single computer as morethan one computer may perform the act.

The example embodiments described herein can be used with computerhardware and software that perform the methods and processing functionsdescribed herein. The systems, methods, and procedures described hereincan be embodied in a programmable computer, computer-executablesoftware, or digital circuitry. The software can be stored oncomputer-readable media. For example, computer-readable media caninclude a floppy disk, RAM, ROM, hard disk, removable media, flashmemory, memory stick, optical media, magneto-optical media, CD-ROM, etc.Digital circuitry can include integrated circuits, gate arrays, buildingblock logic, field programmable gate arrays (FPGA), etc.

The example systems, methods, and acts described in the embodimentspresented previously are illustrative, and, in alternative embodiments,certain acts can be performed in a different order, in parallel with oneanother, omitted entirely, and/or combined between different exampleembodiments, and/or certain additional acts can be performed, withoutdeparting from the scope and spirit of various embodiments. Accordingly,such alternative embodiments are included in the scope of the followingclaims, which are to be accorded the broadest interpretation so as toencompass such alternate embodiments.

Although specific embodiments have been described above in detail, thedescription is merely for purposes of illustration. It should beappreciated, therefore, that many aspects described above are notintended as required or essential elements unless explicitly statedotherwise. Modifications of, and equivalent components or actscorresponding to, the disclosed aspects of the example embodiments, inaddition to those described above, can be made by a person of ordinaryskill in the art, having the benefit of the present disclosure, withoutdeparting from the spirit and scope of embodiments defined in thefollowing claims, the scope of which is to be accorded the broadestinterpretation so as to encompass such modifications and equivalentstructures.

What is claimed is:
 1. A computer-implemented method to infer purchases,comprising: transmitting, by one or more computing devices, an offer toa user computing device, the one or more computing devices not takingpart in approvals of financial transactions and not participating inredemption offers; determining, by the one or more computing devices,that the user interacted with the offer via the user computing device;displaying, by an application executing on the user computing device,the offer on a user interface of the user computing device; displaying,by the application executing on the user computing device, an accountidentifier on the user interface of the user computing device;detecting, by the application executing on the user computing device, ageolocation of the user computing device when the account identifier isdisplayed on the user interface and responsive to displaying the accountidentifier on the user interface; determining, by the applicationexecuting on the user computing device, a first time when the accountidentifier is displayed on the user interface and responsive todisplaying the account identifier on the user interface; transmitting,by the application executing on the user computing device, anotification to the one or more computing devices when the accountidentifier is displayed on the user interface and responsive todisplaying the account identifier on the user interface, thenotification comprising an indication that the account identifier wasdisplayed, the detected geolocation, the determined first time, and adescription of the account identifier; receiving, by the one or morecomputing devices, the notification from the application executing onthe user computing device when the account identifier is displayed onthe user interface of the user computing device; receiving, by the oneor more computing devices, a second notification from an accountcomputing system when a balance is adjusted, the second notificationcomprising an indication that the account balance was adjusted, a secondtime when the balance is adjusted and a description of the balance;determining, by the one or more computing devices, that the indicationthat the account identifier was displayed and the indication that thebalance was adjusted are pre-determined inputs used for identifyingpurchase transactions; determining, by the one or more computingdevices, that the user participated in a purchase transaction with amerchant using a predictive model to analyze the indication that theaccount identifier was displayed, the detected geolocation, thedetermined first time, the second time, and the indication that thebalance was adjusted determining, by the one or more computing devices,that the offer was redeemed during the purchase transaction, the one ormore computing devices not taking part in an approval of the purchasetransaction and not participating in redemption of the offer; andmarking, by the one or more computing devices, the offer as redeemed inresponse to determining that the offer was redeemed during the purchasetransaction.
 2. The method of claim 1, wherein the account identifierdisplayed by the user computing device comprises a loyalty accountidentifier.
 3. The method of claim 1, wherein the account identifierdisplayed by the user computing device comprises a financial accountidentifier.
 4. The method of claim 1, wherein the balance adjusted is agift card balance.
 5. The method of claim 1, wherein the balanceadjusted is a loyalty account balance.
 6. The method of claim 1, furthercomprising receiving, by the one or more computing devices, a thirdnotification comprising a receipt record.
 7. The method of claim 6,wherein determining that the user participated in the purchasetransaction with the merchant further comprises analyzing, by the one ormore computing devices, the receipt record.
 8. The method of claim 1,further comprising: determining, by the one or more computing device, asecond offer to distribute to the user computing device based on thedetermination that the offer was redeemed during the purchasetransaction with the merchant; and transmitting, by one or morecomputing devices, the second offer to the user computing device.
 9. Asystem to infer purchase transactions, comprising: a user computingdevice, the user computing device comprising a first storage devicehaving first application code instructions stored therein, and a firsthardware processor communicatively coupled to the first storage device,wherein the first application code instructions, when executed by thefirst hardware processor, cause the user computing device to: display anoffer on a user interface of the user computing device; display anaccount identifier on the user interface of the user computing device;detect a geolocation of the user computing device when the accountidentifier is displayed on the user interface and responsive todisplaying the account identifier on the user interface; determine afirst time when the account identifier is displayed on the userinterface and responsive to displaying the account identifier on theuser interface; transmit a notification to an account managementcomputing system when the account identifier is displayed on the userinterface and responsive to displaying the account identifier on theuser interface, the notification comprising an indication that theaccount identifier was displayed, the detected geolocation, thedetermined first time, and a description of the account identifier; anaccount computing system, the account computing system comprising asecond storage device having second application code instructions storedtherein, and a second hardware processor communicatively coupled to thesecond storage device, wherein the second application code instructions,when executed by the second hardware processor, cause the accountcomputing system to: detect a second time when a balance is adjusted;transmit a second notification to the account management computingsystem when the balance is adjusted and responsive to the detection ofthe balance being adjusted, the second notification comprising anindication that the balance was adjusted, the second time, and adesertion of the balance; an account management computing system, theaccount management computing system not taking part in the approval offinancial transactions and not participating in redemptions of offers,the account management computing system comprising a storage devicehaving application code instructions stored therein, and a hardwareprocessor communicatively coupled to the storage device, whereinapplication code instructions, when executed by the hardware processor,cause the account management computing system to: determine that a userinteracted with the offer via the user computing device; receive thenotification from the user computing device when the account identifieris displayed by the user interface of the user computing device; receivethe second notification from the account computing system when thebalance is adjusted; determine that the indication that the accountidentifier was displayed and the indication that the balance wasadjusted are pre-determined signals used for identifying purchasetransactions; determine that the user participated in a purchasetransaction with a merchant using a predictive model to analyze theindication that the account identifier was displayed, the detectedgeolocation, the determined first time, the second time, and theindication that the balance was adjusted; determine that the offer wasredeemed during the purchase transaction with the merchant without theone or more computing devices taking part in an approval of the purchasetransaction and without participating in redemption of the offer; andmark the offer as redeemed in response to determining that the offer wasredeemed during the purchase transaction with the merchant.
 10. Thesystem of claim 9, wherein the account identifier displayed. by the usercomputing device comprises a loyalty account identifier.
 11. The systemof claim 9, wherein the account identifier displayed. by the usercomputing device comprises a financial account identifier.
 12. Thesystem of claim 9, wherein the balance adjusted is a gift card balanceor a loyalty account balance.